Applied AI Software Engineer（moment）

Employment information

Job Description

About Cookpad

Cookpad is a food tech company dedicated to shaping the future of home cooking and food as a pillar for a sustainable future. We have been developing innovative product ideas and we have a new product launch in 5 countries: Japan, Indonesia, UK, France and Italy.

moment helps people learn to cook in an innovative way with a personal coaching service. This service is completely based in AI using multimodal (text, vision, audio).

 

About the role

Joining Cookpad as an Applied AI Engineer you will be asked to solve interesting problems associated with turning machine learning models into a service. This will include building functionalities that need to be implemented in order to ensure fully production-ready code. You will communicate ideas and demos to team members and take ownership of how a feature is productionised, built and deployed. You will be highly proficient in coding in Python and have proven hands-on experience in building applications and integrations of modern generative AI models. It’s not for everyone. Because of our speed and growth, it can feel chaotic. We work in a small, collaborative team and in a creative, fast-paced environment. Initially our focus is small scale production. The role is based in Tokyo and we are happy to hear from applicants seeking either full-time contract or permanent employment.

 

Key Responsibilities

• Leverage cutting-edge AI technologies to address real-world customer challenges.
• Collaborate with product team to translate business and product requirements into technical solutions that leverage the latest in AI technologies.
• Design and implement intelligent AI agents and multi-agent systems capable of autonomous decision-making and interaction, enabling complex workflows and real-time problem-solving.
• Develop agent-based architectures for applications such as task orchestration, adaptive learning, and dynamic data analysis.
• Create and deploy Retrieval-Augmented Generation (RAG) systems to enhance AI model retrieval and contextual response accuracy.
• Evaluate and refine prompt engineering strategies, incorporating advanced techniques to optimize generative model outputs for diverse use cases.

Qualifications

• Solid professional software engineering background.
• Approx. 5+ years industry experience in software development -Strong Python skills, including production-level experience
• Proficiency in modern software engineering best practices e.g. test-driven development, version control, CI / CD, containerisation
• Hands-on experience building applications and integrations with modern generative AI models (e.g., LLMs).
• Hands-on experience with advanced techniques for optimizing generative model outputs.
• Ability to work effectively both independently and within a team.
• Proven ability to perform in a dynamic, fast-paced environment.
• Strong analytical and problem-solving abilities.
• Ability to communicate effectively in English within the team

Preferred Qualifications

• Strong foundation in AI/ML principles, with a focus on Generative AI and Large Language Models (LLMs).
• Ground understanding of the trade-offs, capabilities, and limitations of different AI models.
• Experience with vector embeddings and working with vector databases (e.g., Pinecone).
• Experience in integrating data with pre-trained Generative AI models using techniques like RAG and fine-tuning, utilizing tools such as LangChain, LlamaIndex, Hugging Face, AWS Bedrock, or Google Vertex AI.
• Experience with at least one common cloud provider (AWS, GCP, Azure).
• Knowledge of MLOps/LLMOps practices, including model deployment, serving, and monitoring.
• Familiarity with data engineering principles and managing data pipelines for AI applications.